Data Architect Snowflake

Role: Senior Data Architect

Location: Remote 

Role Summary:

We are seeking a Senior Data Architect with deep experience in institutional financial accounting systems and cloud-native data platforms. You will own the requirements and design of a multi-source canonical data model (CADM) spanning accounting, risk, and performance data domains, and will be responsible for maintaining and evolving those designs across a full delivery lifecycle as new requirements, sources, and product versions emerge. 
This is a hands-on, specification-led role. You will produce the authoritative data model artifacts that engineering teams build from, working directly with product owners, solution architects, and source system SMEs. 

Key Responsibilities: 

Canonical Data Model Design 
Own the design of the Common Analytics Data Model (CADM) — a system-agnostic Layer 2 hub that normalizes inputs from multiple accounting sources into a unified schema consumable by all downstream products. 
Define and document a three-layer architecture: Layer 1 (source models) → Layer 2 (canonical hub) → Layer 3 (semantic/application), with clear interface contracts at each boundary. 
Design Lifecycle Management 
Maintain and evolve data model designs across multiple delivery phases and product versions — managing schema changes, field deprecations, and structural extensions without breaking existing downstream consumers. 
Define and enforce a versioning strategy for the CADM and all interface specifications, ensuring that engineering teams, product owners, and downstream applications always reference a clearly versioned, authoritative design. 

Financial Accounting System Integration 
Design a common source interface pattern enabling accounting platforms to be onboarded incrementally with minimal redesign. 

Snowflake Architecture 
Design the Snowflake materialization strategy across all layers: determine what is virtualized vs. materialized, and the appropriate use of dynamic tables, Snowpark, and materialized views. 
Design Layer 3 Power BI semantic models (star schema): fact tables for positions and exposures, dimension tables for security, account, date, geography, and sector. 
Risk Engine Data Architecture 
Analyze risk engine input specifications and define a standard data feed model mapping CADM positions, prices, security master data, and Over the Counter (OTC) terms and conditions to risk engine inputs. 
Design the risk results storage model in Snowflake: fact tables for Value at Risk (VaR) outputs, stress scenario results, and factor exposures, with versioning and scenario identification metadata. 
Performance & Third-Party Data Integration 
Align the Performance application data model with the shared CADM — define shared schema elements and interface contracts to eliminate duplication across products. 
Define the ingestion approach for third-party performance data: favor shared CADM adapters for non-pervasive sources. 

Engineering Handoff & Documentation 
Produce engineering-ready specifications for all deliverables: business context, data model definitions, transformation rules, Snowflake/Vault engineering requirements, and acceptance criteria. 
Document all designs in Confluence aligned to engineering intake processes, ensuring specifications are structured for direct consumption by internal engineering pods. 
Participate in and facilitate architecture alignment workshops with client solution architects and Professional Services teams.

Required Qualifications 
Financial Accounting Systems 
Significant hands-on experience with one or more institutional investment accounting platforms. 
Deep understanding of Accounting Book of Record (ABOR) and Investment Book of Record (IBOR) data models: differences in timing, completeness, position sourcing, and downstream use. 
Experience with complex instrument representation: multi-leg derivatives, fund-of-fund look-through, private market holdings, OTC contracts. 
Experience normalizing data across multiple accounting sources into a unified canonical schema — resolving structural and semantic differences between systems. 

Snowflake & Cloud Data Platforms 
Production experience designing and implementing layered data architectures in Snowflake: 
Materialization strategy: dynamic tables, Snowpark, materialized views, virtual layers 
Star schema and semantic layer design for Business Intelligence (BI) consumption (Power BI, Tableau) 
Compute cost design: query optimization, clustering, partition strategy, billing-aware architecture 
Snowpark for Python/Scala-based in-platform computation 
Experience with medallion / layered architecture (Bronze/Silver/Gold or equivalent) with clearly defined interface contracts between layers. 


Data Architecture & Modeling 
10+ years of data architecture experience, with a focus on canonical and enterprise data modeling in financial services. 
Proven ability to design source-agnostic data models that accommodate multiple upstream systems without requiring schema redesign. 
Experience producing formal design artifacts: entity-relationship diagrams, field-level specifications, transformation rules, and Level 1/2 field classifications. 
Strong grasp of data normalization principles, join key design, audit trail attributes, and lineage patterns. 
Demonstrated experience maintaining and evolving data model designs across a multi-phase delivery lifecycle — managing versioning, backward compatibility, deprecation, and controlled schema evolution as product requirements grow. 
Experience in asset management, wealth management, or institutional banking data domains: positions, transactions, securities, benchmarks, performance, and/or risk. 
Design Lifecycle & Governance 
Experience versioning data models and interface specifications across multiple releases, including strategies for non-breaking field additions, deprecation paths, and controlled breaking changes. 
Experience authoring and maintaining Architecture Decision Records (ADRs) as a living governance artifact across a long-running engagement. 
Ability to assess the downstream impact of new requirements on existing designs and communicate change risk clearly to engineering and product stakeholders. 
Experience establishing and enforcing documentation standards so that design artifacts remain accurate and current as implementations evolve. 
Communication & Delivery 
Ability to translate complex technical architecture into clear, engineering-ready specifications consumable by development pods without direct oversight. 
Comfortable working directly with senior product owners, solution architects, and technology leads in a consulting or embedded advisory capacity. 
Experience documenting in Confluence; familiarity with Jira / POM-style backlog management and engineering intake processes. 
Effective at facilitating architecture alignment sessions across distributed, multi-stakeholder teams.